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Wrangle weight-for-height data

Source: R/wrangle_wfhz.R
mw_wrangle_wfhz.Rd

Calculate z-scores for weight-for-height (WFHZ) and identify outliers based on the SMART methodology.

Usage

mw_wrangle_wfhz(df, sex, weight, height, .recode_sex = TRUE, .decimals = 3)

Arguments

df

A data.frame object to wrangle data from.

sex

A numeric or character vector of child's sex. Code values should only be 1 or "m" for males and 2 or "f" for females.

weight

A vector of class double of child's weight in kilograms.

height

A vector of class double of child's height in centimeters.

.recode_sex

Logical. Set to TRUE if the values for sex are not coded as 1 (for males) or 2 (for females). Otherwise, set to FALSE (default).

.decimals

The number of decimal places to use for z-score outputs. Default is 3.

Value

A data frame based on df with new variables named wfhz for child's WFHZ and flag_wfhz for detected outliers added.

References

SMART Initiative (2017). Standardized Monitoring and Assessment for Relief and Transition. Manual 2.0. Available at: https://smartmethodology.org.

See also

flag_outliers() remove_flags()

Examples

mw_wrangle_wfhz(
  df = anthro.01,
  sex = sex,
  weight = weight,
  height = height,
  .recode_sex = TRUE,
  .decimals = 2
)
#> ================================================================================
#> # A tibble: 1,191 × 13
#>    area      dos        cluster  team   sex dob      age weight height edema
#>    <chr>     <date>       <int> <int> <dbl> <date> <int>  <dbl>  <dbl> <chr>
#>  1 District… 2023-12-04       1     3     1 NA        59   15.6  109.  n    
#>  2 District… 2023-12-04       1     3     1 NA         8    7.5   68.6 n    
#>  3 District… 2023-12-04       1     3     1 NA        19    9.7   79.5 n    
#>  4 District… 2023-12-04       1     3     2 NA        49   14.3  100.  n    
#>  5 District… 2023-12-04       1     3     2 NA        32   12.4   92.1 n    
#>  6 District… 2023-12-04       1     3     2 NA        17    9.3   77.8 n    
#>  7 District… 2023-12-04       1     3     2 NA        20   10.1   80.4 n    
#>  8 District… 2023-12-04       1     3     2 NA        27   11.7   87.1 n    
#>  9 District… 2023-12-04       1     3     1 NA        46   13.6   98   n    
#> 10 District… 2023-12-04       1     3     1 NA        58   17.2  109.  n    
#> # ℹ 1,181 more rows
#> # ℹ 3 more variables: muac <int>, wfhz <dbl>, flag_wfhz <dbl>